Filessuch

Filessuch is a fictional framework for describing and locating files that match a defined set of attributes or content patterns. It is used here to illustrate how a metadata-driven search system might operate across diverse file stores, including personal libraries and organizational repositories.

Core concepts in filessuch include a metadata schema, content-based similarity, and a query language. The metadata schema combines standard fields such as filename, mime type, size, creation and modification dates with user-defined tags, relationships, and provenance information. Content-based similarity uses multiple signals: checksums or perceptual hashes for non-text content, and vector-based embeddings or textual fingerprints for documents, enabling queries like “files such as this” or “similar to” a given item. The query language supports filters by type, tags, date ranges, and relational attributes, and can combine conditions with boolean operators and ranking hints.

Architecture and workflow typically involve three stages. Indexing collects and stores metadata and content signatures from each file, creating a searchable index. Querying interprets user input, evaluates it against the index, and retrieves candidate matches. Results are ranked by a combination of relevance, similarity score, and provenance quality, then returned for user refinement.

Relationship to real-world systems: filessuch is not an established standard. It synthesizes ideas from digital asset management, metadata repositories, and content-based retrieval. In practice, a filessuch-like capability could be implemented as a modular layer within existing file systems or integrated into digital libraries and enterprise search tools.

Example usage includes locating all image files tagged “landscape” created after 2020 that are similar to a reference image, or finding documents of a certain genre that resemble a given exemplar.